Excitation energy transfer pathways in light-harvesting proteins: Modeling with PyFREC

Excitation energy transfer (EET) determines the fate of sunlight energy absorbed by light-harvesting proteins in natural photosynthetic systems and photovoltaic cells. As previously reported (D. Kosenkov, J. Comput. Chem. 2016, 37(19), 1847), PyFREC software enables computation of electronic couplings between organic molecules with a molecular fragmentation approach. The present work reports implementation of direct fragmentation-based computation of the electronic couplings and EET rates in pigment-protein complexes within the Forster theory in PyFREC. The new feature enables assessment of EET pathways in a wide range of photosynthetic complexes, as well as artificial molecular architectures that include light-harvesting proteins or tagged fluorescent biomolecules. The developed methodology has been tested analyzing EET in the Fenna-Matthews-Olson (FMO) pigment-protein complex. The pathways of excitation energy transfer in FMO have been identified based on the kinetics studies. (c) 2017 Wiley Periodicals, Inc.